Although conversational AI has been in the headlines for years now, B2C applications of this technology are still in their infancy. I believe that's going to change this year, and we're going to see conversational interfaces replace more websites, mobile apps and contact centers than ever before — even as the burgeoning industry faces new challenges.

I work with large enterprises looking to add conversational AI to their customer experience, so I've seen the signs that a boom is on the way. One strong indicator is the amount of funding pouring into the space. We've seen a growing number of VCs investing in conversational AI startups, with some luminaries — like the founder of SoftBank, Masayoshi Son — focusing almost entirely on AI. We’ve also seen legacy technology vendors attempt to do chatbot bolt-ons to stay relevant, but they’ve had trouble competing with upstarts that are fundamentally built around “conversationalizing” a business with automation. That's one reason giants like Microsoft, SAP and Cisco have acquired conversational AI startups. Many of the world’s largest enterprises are in the process of digital transformation — not by election, but for survival.

The dollars are there. But what’s going to ultimately make 2019 the year of conversational interfaces has more to do with recent developments in technology, consumer preferences and economic drivers.

Technical Advances Lead To New Adoption

Across the board, technical barriers to conversational AI are breaking down. For one, the emergence of self-service platforms makes conversational AI easier to implement. For those that sit atop a robust infrastructure, it's now possible for conversational AI to be implemented securely, with support for data redaction and encryption and in compliance with GDPR, HIPAA and PCI. Many conversational AI solutions also integrate with back-end systems via APIs to deliver transactional utility and authenticate users via standards like OAuth.

In addition to the easier implementation, enterprises are also seeing the data benefits of conversational interfaces versus their website counterparts. Conversational data, thanks to the depth of user preferences revealed during an interaction, can be much more actionable than website data. Furthermore, agent-led chats create training data for conversational AI, helping automated experiences continually improve in quality.

And then there’s the issue of speed. The average time it takes to fully load a mobile landing page is 22 seconds, but 53% of mobile site visitors leave a page that takes longer than three seconds to load. In contrast, automated conversational interfaces run on technology with an instant response mechanism. I find they’re easier to navigate and particularly suitable for customer service situations in which users don’t want to — or won’t — wait.

At a psychological level, conversational AI can overcome consumers’ main frustrations with reaching out to a company. They can provide private, instant access to transactional features, and rather than presenting intimidating forms of 40+ fields to populate, conversational AI can tease out one piece of information at a time to keep the user focused on the immediate step in resolving their specific challenge.

Such automated interfaces can also enable rich, immersive experiences with tools like videos and GIFs, which help to reduce the cognitive weight of even having to type. With effective automated journey design and enough automation scope, conversational AI has the potential to bring consumers a 24/7, always-on gateway to a business.

The Economics Bear Out

Let’s not forget the economics that drive enterprises to adopt automation in the first place. Given that so many web chat agents read from decision trees and scripts, there are a lot of components of customer service messaging that can easily be automated. A single call to a contact center can cost an enterprise as much as $6 to $15 (or even as much as $41) to answer basic questions about the status of an account or how to reset a password. At scale, conversational AI can create up to a 90% reduction in costs. In addition, we’ve even seen evidence that conversational commerce interactions convert at a higher rate than websites.

Challenges Remain In 2019

Benefits aside, the conversational AI space will face a few ongoing challenges. This includes confusion with (and backlash against) chatbots. Many in the marketplace use “chatbots" and “conversational AI” interchangeably, but the differences run deep. As resistance grows against basic, single-task chatbot experiences, conversational AI needs to distinguish itself as the deeper, enterprisewide solution that it is.

Moreover, conversational AI cannot transform user experiences with broken business processes. It can solve a range of problems for organizations, but if it is applied on top of a weak organizational structure, it can accentuate the underlying flaws of a system. Executives looking to employ these solutions need to realize that a certain degree of advance housekeeping is required.

In the wake of GDPR and 2018 data breach headlines, executives are warier than ever of new technology that interfaces with consumer data. People operating in the conversational AI space need to outwardly demonstrate the security underlying these enterprise solutions in order to combat customer data paralysis. So, as the market becomes more educated on what not to do, these challenges will cause fewer headwinds.

A Convergence of Trends

The growing role of automation in business and rapidly shifting consumer expectations are hot topics these days. Conversational AI is where those two mega-trends converge, representing automation’s wide applicability and delivering on new consumer demands. In 2019, I believe we’ll see conversational AI hit an inflection point where it makes sense not only for enterprises, but also for consumers.